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<p>The increasing volume of electronic waste (e-waste) and shortage of critical materials emphasize the need for sustainable management of end-of-life printed circuit boards (PCBs). This study explores the techno-economic feasibility of reusing electronic components (ECs) from discarded PCBs, particularly used&#xa0;in automotive applications. We developed a systematic process involving manual disassembling with hot air guns, followed by a three-stage sorting process involving size-based segregation, magnetic separation, and optical sorting through convolutional neural networks (CNNs). The CNN-based sorting achieved over 99% identification accuracy, and electrical testing confirmed 98% of the components as functional for reuse. Techno-economic analysis of a simulated EC recovery plant showed encouraging financial outcomes, proving profitable even with a conservative resale value of 5–20% of market prices. A techno-economic model for a recovery plant was developed based on bottom-up costing, incorporating disassembly rates, labor productivity, equipment costs, reverse logistics, and resale value assumptions to evaluate break-even time and scalability across geographic regions.&#xa0;The&#xa0;research&#xa0;proved the environmental and economic benefits of integrating EC reuse into circular economy practices, offering a scalable framework for sustainable e-waste management.</p> Graphical Abstract <p></p>

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Techno-economic evaluation of electronic component recovery for reuse from waste PCBs: advancing circular economy practices in automotive electronics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月17日

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  • Pallab Das,
  • Adrian Leonardi,
  • Qingyu Yan,
  • Katharina Peier,
  • Jean-Christophe P. Gabriel

摘要

The increasing volume of electronic waste (e-waste) and shortage of critical materials emphasize the need for sustainable management of end-of-life printed circuit boards (PCBs). This study explores the techno-economic feasibility of reusing electronic components (ECs) from discarded PCBs, particularly used in automotive applications. We developed a systematic process involving manual disassembling with hot air guns, followed by a three-stage sorting process involving size-based segregation, magnetic separation, and optical sorting through convolutional neural networks (CNNs). The CNN-based sorting achieved over 99% identification accuracy, and electrical testing confirmed 98% of the components as functional for reuse. Techno-economic analysis of a simulated EC recovery plant showed encouraging financial outcomes, proving profitable even with a conservative resale value of 5–20% of market prices. A techno-economic model for a recovery plant was developed based on bottom-up costing, incorporating disassembly rates, labor productivity, equipment costs, reverse logistics, and resale value assumptions to evaluate break-even time and scalability across geographic regions. The research proved the environmental and economic benefits of integrating EC reuse into circular economy practices, offering a scalable framework for sustainable e-waste management.

Graphical Abstract